As a general technique for encoding multidimensional distribution data such as a two-dimensional image, a data amount compression technique such as a JPEG compression technique is known. Two-dimensional image data is subjected to discrete cosine transform then quantization, and encoding by the Huffman coding or the like.
Further, a method for predictive-encoding image data, block-dividing prediction error data by the predictive coding, and determining whether or not each block has a large amount of prediction error or small amount of prediction error is known (for example, Japanese Patent Application Laid-Open No. Hei 11-331852). According to the method disclosed by the document, vector quantization is applied to a block with a large amount of prediction error, then the difference value between a vector value of a codebook retrieved by the vector quantization and the prediction error is calculated, then the difference value and the prediction error in a block with a small amount of prediction error are entropy-encoded, and coded data is generated by using the entropy code, a block error-amount discrimination flag and an index by vector quantization. In this manner, from the viewpoint of space-saving data conservation and high-speed communication, a high efficiency data coding technique is desired.
Further, in an arithmetic unit to perform discrete convolution on a two-dimensional image represented by predetermined two-dimensional weight distribution data, which is frequently used in image processing such as filtering, accelerated computation is expected by use of a large-scale parallelized product-sum arithmetic elements. However, the product-sum operation by two-dimensionally parallelized arithmetic elements cannot be realized without difficulty due to wiring problem and the like. Accordingly, a method for decomposing two-dimensional weight distribution data into one-dimensional base group for convolution is desired.